Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART)
Objective:. This study aims to introduce key concepts and methods that inform the design of studies that seek to quantify the causal effect of social determinants of health (SDOH) on access to and outcomes following organ transplant. Background:. The causal pathways between SDOH and transplant outco...
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| Format: | Article |
| Language: | English |
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Wolters Kluwer Health
2023-12-01
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| Series: | Annals of Surgery Open |
| Online Access: | http://journals.lww.com/10.1097/AS9.0000000000000337 |
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| author | Nrupen A. Bhavsar, PhD Rachel E. Patzer, PhD David J. Taber, PharmD Katie Ross-Driscoll, PhD Rhiannon Deierhoi Reed, PhD Juan C. Caicedo-Ramirez, MD Elisa J. Gordon, PhD, MPH Roland A. Matsouaka, PhD Ursula Rogers, BS Wendy Webster, MBA Andrew Adams, MD, PhD Allan D. Kirk, MD Lisa M. McElroy, MD |
| author_facet | Nrupen A. Bhavsar, PhD Rachel E. Patzer, PhD David J. Taber, PharmD Katie Ross-Driscoll, PhD Rhiannon Deierhoi Reed, PhD Juan C. Caicedo-Ramirez, MD Elisa J. Gordon, PhD, MPH Roland A. Matsouaka, PhD Ursula Rogers, BS Wendy Webster, MBA Andrew Adams, MD, PhD Allan D. Kirk, MD Lisa M. McElroy, MD |
| author_sort | Nrupen A. Bhavsar, PhD |
| collection | DOAJ |
| description | Objective:. This study aims to introduce key concepts and methods that inform the design of studies that seek to quantify the causal effect of social determinants of health (SDOH) on access to and outcomes following organ transplant.
Background:. The causal pathways between SDOH and transplant outcomes are poorly understood. This is partially due to the unstandardized and incomplete capture of the complex interactions between patients, their neighborhood environments, the tertiary care system, and structural factors that impact access and outcomes. Designing studies to quantify the causal impact of these factors on transplant access and outcomes requires an understanding of the fundamental concepts of causal inference.
Methods:. We present an overview of fundamental concepts in causal inference, including the potential outcomes framework and direct acyclic graphs. We discuss how to conceptualize SDOH in a causal framework and provide applied examples to illustrate how bias is introduced.
Results:. There is a need for direct measures of SDOH, increased measurement of latent and mediating variables, and multi-level frameworks for research that examine health inequities across multiple health systems to generalize results. We illustrate that biases can arise due to socioeconomic status, race/ethnicity, and incongruencies in language between the patient and clinician.
Conclusions:. Progress towards an equitable transplant system requires establishing causal pathways between psychosocial risk factors, access, and outcomes. This is predicated on accurate and precise quantification of social risk, best facilitated by improved organization of health system data and multicenter efforts to collect and learn from it in ways relevant to specialties and service lines. |
| format | Article |
| id | doaj-art-cea6405c821f4abca8597f4fe5f86bde |
| institution | Kabale University |
| issn | 2691-3593 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Wolters Kluwer Health |
| record_format | Article |
| series | Annals of Surgery Open |
| spelling | doaj-art-cea6405c821f4abca8597f4fe5f86bde2025-01-24T09:18:11ZengWolters Kluwer HealthAnnals of Surgery Open2691-35932023-12-0143e33710.1097/AS9.0000000000000337202312000-00001Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART)Nrupen A. Bhavsar, PhD0Rachel E. Patzer, PhD1David J. Taber, PharmD2Katie Ross-Driscoll, PhD3Rhiannon Deierhoi Reed, PhD4Juan C. Caicedo-Ramirez, MD5Elisa J. Gordon, PhD, MPH6Roland A. Matsouaka, PhD7Ursula Rogers, BS8Wendy Webster, MBA9Andrew Adams, MD, PhD10Allan D. Kirk, MD11Lisa M. McElroy, MD12From the * Department of Medicine, Duke University School of Medicine, Durham, NC‡ Department of Surgery, Emory University School of Medicine, Atlanta, GA§ Department of Surgery, Medical University of South Carolina, Charleston, SC‡ Department of Surgery, Emory University School of Medicine, Atlanta, GA‖ Department of Surgery, The University of Alabama at Birmingham, Birmingham, AL¶ Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL# Department of Surgery, Vanderbilt University Medical Center, Nashville, TN† Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC** Department of Surgery, Duke University School of Medicine, Durham, NC** Department of Surgery, Duke University School of Medicine, Durham, NC†† Department of Surgery, University of Minnesota Medical School, Minneapolis, MN.** Department of Surgery, Duke University School of Medicine, Durham, NC** Department of Surgery, Duke University School of Medicine, Durham, NCObjective:. This study aims to introduce key concepts and methods that inform the design of studies that seek to quantify the causal effect of social determinants of health (SDOH) on access to and outcomes following organ transplant. Background:. The causal pathways between SDOH and transplant outcomes are poorly understood. This is partially due to the unstandardized and incomplete capture of the complex interactions between patients, their neighborhood environments, the tertiary care system, and structural factors that impact access and outcomes. Designing studies to quantify the causal impact of these factors on transplant access and outcomes requires an understanding of the fundamental concepts of causal inference. Methods:. We present an overview of fundamental concepts in causal inference, including the potential outcomes framework and direct acyclic graphs. We discuss how to conceptualize SDOH in a causal framework and provide applied examples to illustrate how bias is introduced. Results:. There is a need for direct measures of SDOH, increased measurement of latent and mediating variables, and multi-level frameworks for research that examine health inequities across multiple health systems to generalize results. We illustrate that biases can arise due to socioeconomic status, race/ethnicity, and incongruencies in language between the patient and clinician. Conclusions:. Progress towards an equitable transplant system requires establishing causal pathways between psychosocial risk factors, access, and outcomes. This is predicated on accurate and precise quantification of social risk, best facilitated by improved organization of health system data and multicenter efforts to collect and learn from it in ways relevant to specialties and service lines.http://journals.lww.com/10.1097/AS9.0000000000000337 |
| spellingShingle | Nrupen A. Bhavsar, PhD Rachel E. Patzer, PhD David J. Taber, PharmD Katie Ross-Driscoll, PhD Rhiannon Deierhoi Reed, PhD Juan C. Caicedo-Ramirez, MD Elisa J. Gordon, PhD, MPH Roland A. Matsouaka, PhD Ursula Rogers, BS Wendy Webster, MBA Andrew Adams, MD, PhD Allan D. Kirk, MD Lisa M. McElroy, MD Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) Annals of Surgery Open |
| title | Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) |
| title_full | Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) |
| title_fullStr | Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) |
| title_full_unstemmed | Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) |
| title_short | Defining the Need for Causal Inference to Understand the Impact of Social Determinants of Health: A Primer on Behalf of the Consortium for the Holistic Assessment of Risk in Transplantation (CHART) |
| title_sort | defining the need for causal inference to understand the impact of social determinants of health a primer on behalf of the consortium for the holistic assessment of risk in transplantation chart |
| url | http://journals.lww.com/10.1097/AS9.0000000000000337 |
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